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The use of remotely sensed data to estimate forest attributes involves the acquisition of ground
forest data. Recently the acquisition of ground data (field based) to estimate leaf area index (LAI)
and biomass are becoming expensive and time consuming. Thus there is a need for an easy but yet
effective means of predicting the LAI, which serves as an input to the forest growth prediction
models and the quantification of water use by forests. The ability to predict LAI, biomass and
eventually water use over a large area remotely using remotely sensed data is sought after by the
forestry companies. Remotely sensed LAI values provide the opportunity to gain spatial information
on plant biophysical attributes that can be used in spatial growth indices and process based growth
models. In this study remotely sensed images were transformed into LAI value estimates, through
the use of four vegetation indices (Normalized Difference Vegetation Index (NDVI), Corrected
Normalized Difference Vegetation Index (NDVlc), Ratio Vegetation Index (RVI) and Normalized
Ratio Vegetation Index (NRVI). Ground based measurements (Destructive Sampling and Leaf
Canopy Analyzer) relating to LAI were obtained in order to evaluate the vegetation indices value
estimates. All four vegetation indices values correlated significantly with the ground-based
measurements, with the NDVI correlating the highest. These results suggested that NDVI is the best
in estimating the LAI in Eucalyptus grandis x camaldulensis in the Zululand region with correlation
coefficients of 0.78 for destructive sampling and 0.75 for leaf canopy analyzer. Visual inspection of
scatter plots suggested that the relations between NDVI and ground based measurements were
variable, with R2 values of 0.61 for destructive sampling and 0.55 for Leaf Canopy analyzer. These
LAI estimates obtained through remotely sense data showed a great promise in South African
estimation of LAI values of Eucalyptus grandis x camaldulensis. Thus water use and biomass can
be quantified at a less expensive and time-consuming rate but yet efficiently and effectively.

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